Robust and efficient estimation of hidden state variables of a system in the presence of measurement noise and modeling errors is crucial for online model based fault diagnosis of continuous systems. Dynamic Bayesian Networks (DBNs) provide generalized and systematic methods for reasoning under uncertainty. This paper presents an approach to improve estimation efficiency by partitioning the DBN...

To address sparse channel estimation problem in nonGaussian impulsive noise environment, a recursive maximum correntropy criteria (RMCC) algorithm using sparse constraint is proposed to combat impulsive-inducing instability. Specifically, the recursive algorithm on the correntrioy with a forgetting factor of error at iteration is to solve steady-state error for improving the maximum correntropy...

We investigate properties of Bayesian networks (BNs) in the context of robust state estimation. We focus on problems where state estimation can be viewed as a classification of the possible states, which in turn is based on the fusion of heterogeneous and noisy information. We introduce a coarse perspective of the inference processes and show that classification with BNs can be very robust, eve...

If we try to estimate the parameters of the AR process {Xn} using the observed process {Xn+Zn} then these estimates will be badly biased and not consistent but we can minimize the damage using a robust estimation procedure such as GM-estimation. The question is does additive contamination affect estimates of “core” parameters in the infinite variance case to the same extent that it does in the ...

Co-registered intensity and range imaging is one example of complementary multi-modality that has been extensively explored for 3D reconstruction, yet not fully researched for robust estimation. The classic RANdom SAmple Consensus and its variants such as PROSAC, Preemptive RANSAC and SCRAMSAC, to name a few, have been the most commonly applied approaches to visionbased homography estimation, w...

With a focus on investigations in the area of overactuated spacecraft, a new high-performance robust three-axis finite-time attitude control approach, which is organized in connection with the quaternion based estimation scheme is proposed in the present research with respect to state-of-the-art. The approach proposed here is realized based upon double closed loops to deal with the angular rate...

this paper presents a discrete-time robust control for electrically driven robot manipulators in the task space. a novel discrete-time model-free control law is proposed by employing an adaptive fuzzy estimator for the compensation of the uncertainty including model uncertainty, external disturbances and discretization error. parameters of the fuzzy estimator are adapted to minimize the estimat...